Abstract
Minimizing production of water from gas reservoirs is one of the main strategies for enhancing primary hydrocarbon production. Advances in intelligent well technology and simulation of reservoir-production system enable optimum inflow allocation of produced fluids by controlling perforations and valve settings. However, real-time optimum control of flow is still a challenge. To this end, we have developed an advanced method for optimization of production based on a feed-back optimum control concept. The method allows optimization of inflow-control–device operation in conjunction with strategic updating of reservoir-smart well model under uncertainty.
In this work, we present a hybrid optimization method for improving optimum solutions. In this method, the response of production system to control variables is mathematically described by a high-order proxy model, which is developed using Response Surface Methodology (RSM) and Design of Experiments (DOE). The validity of this method was tested for the dynamic optimum control of gas and water coning observed in a physical two-dimensional layered bead-pack model with automatic inflow control valves. The valves were actuated by distributed flow or pressure sensors. Results showed that dynamic (time-dependent valve settings) and static (fixed valve setting) control exhibited advantages one over another, depending on operational conditions. It was also found that the heterogeneity of porous media strongly influenced the control effectiveness. Field implications are discussed.
